This is the first talk from the 3rd International Workshop on Adaptive Case Management and Non-Workflow BPM. conference overview at: http://acm2014.blogs.dsv.su.se/

1. Keith D Swenson
Sept 2014
Ulm, Germany
AdaptiveCM Workshop 2014 Keynote: status of the field so far

2. Innovation
refers to the introduction of novel ideas or methods.

4. Knowledge workers
… high degree of expertise,
… involves the creation, distribution,
or application of knowledge.
- Thomas Davenport

5. Knowledge worker productivity
is the biggest of the
21st century management challenges.
In the developed countries
it is their first
survival
requirement.
- Peter F Drucker

6. By a number of estimates,
•intellectual property,
•brand value,
•process know-how, and
•other manifestations of brain power generated more than 70% of all US market value created over the past three decades. - “The Productivity Imperative”, McKinsey and Company

7. “The System”
Your
Organization
IT
System
&
People
Offices
Agreements
Skills
Expertise
Relationships
Hardware Software Data
Desire to optimize the entire system

8. Definition of BPM
Business Process Management (BPM) is a discipline involving any combination of modeling, automation, execution, control, measurement and optimization of business activity flows, in support of enterprise goals, spanning systems, employees, customers and partners within and beyond the enterprise boundaries.

9. Application Dev
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents
& Unstructured
Data
Databases &
Structured
Data

10. Dependencies
Unpredictable does not mean Random
Weather is unpredictable, but not random
Weather is predictable, but only a few days in advance
Predictability is related to Dependencies
Something that is “independent” is self contained and generally predictable.
Something that is dependent on a small number of external things might be predictable to the extent that the external things are predictable
Something dependent on large numbers of external things, or dependent upon unpredictable things, generally can’t be predicted
Look for the amount of external dependency

11. Closed Systems
Even a closed system with no external dependencies can be unpredictable.
lots of internal dependencies
iterations over and over
overly sensitive responses
Unpredictability is when the number of variables overwhelm the possibilities.
This is known as chaos
but it is not random
It is not just that you don’t know the status well enough to predict, but that it is impossible to know the status that well

12. Repeatability
Repeatable = Predictable
perfectly repeating == perfectly predictable
Can be differences, and still be repeatable
Everything is predictable the moment before it happens
It is about the amount of time ahead.
this is the prediction horizon
If the process lasts longer than the prediction horizon, then we call it unpredictable.
It can not be predefined, and must be managed “on the fly”

13. Examples of Predictability Types
Predictability
Description
Change Horizon
Work Duration
Very High
Factory Work
Many years
Minutes to days
Very high
Food Preparation
Many years
minutes
High
Server Integration
Years
Minutes
Medium
Order fulfillment
Weeks to months
Minutes to hours
Low
Social Work
Weeks to years
Weeks to years
Very low
Medical treatment
Days to weeks
Weeks to years
Very low
Detective
Hours to weeks
Weeks to years

14. It is all about time
Unstructured
Late-structured

15. Application Dev
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents
& Unstructured
Data
Databases & Structured Data
Development Investment High Low End User Effort Low High Cost to Modify High Low Control of Process High Low

16. Application Dev
Process Technology
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases & Structured Data

17. Application Dev
PDS Integration
Human PM
Production CM
Adaptive CM
Social Biz
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases & Structured Data

18. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases &
Structured
Data
Traditional Programming model Java C++ C# Design, develop, test, release Very robust Very Scalable and Performant Costly to develop

19. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents
& Unstructured
Data
Databases & Structured Data
Design using a process model Easier to explain to business people Easier to change and modify Still mainly about server to server integration, data flows BPEL, Straight-Thru-Processing

20. Application Dev
PDS Integration
Human PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Human PM
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases &
Structured
Data
Design using a process model Model automatically takes care of things that people do:
•reminders
•reassignment
•delegation
•escalations
•roles
•deadlines
Easier to explain to business people Easier to change and modify

21. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Production CM
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases & Structured Data
Production Case Mgmt
Design using a case model, but for knowledge worker
Processes are more like menu choices
Data is center High volume Knowledge Worker for hire Design remains separate from users

22. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Adaptive CM
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases & Structured Data
Not designed using a model, but simply styled by the knowledge worker. Guidelines NOT guardrails Designed data objects Checklists
More documents
More msgs and notes
Less DB use
Planning is part of the work

23. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Social Biz
Variable, Unique
Predictable, Repeatable
Notes
Documents
& Unstructured
Data
Databases & Structured Data
Less customizable, More basic capabilities Special purpose cloud based collaborative applications
•eVite, event bright
•Discussion forums
•Wiki
•Basic CMS

24. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases & Structured Data
Traditional communications only,
No structure
All message and attachments

25. Application Dev
PDS Integration
Human PM
Production CM
Adaptive CM
Social Biz
Email, Texting, Twitter, Telephone
Variable, Unique
Predictable, Repeatable
Notes
Documents & Unstructured Data
Databases &
Structured
Data

26. Application Dev
PDS Integration
Human PM
PCM
ACM
SBS
Email, Texting, Twitter, Telephone
Production CM
Adaptive CM
Scripted and Enforced Process
Little or
No Defined
Process

27. History
1990’s Workflow, Business ProcessReengineering
2000’s Business Process Management
2010 – Emergence of Adaptive Case Management
Mastering the Unpredictable
2011, 2012, 2013, 2014 – Adaptive Case Management Excellence Awards – 38 Use Cases Documented
Taming the Unpredictable, How Knowledge Workers get things done, Empowering Knowledge Workers, and a new one…
2012-2013 AdaptiveCM Workshop 1 & 2
Now: AdaptiveCM 2014

28. Workflow Management Coalition
•Standards
•Books
•Awards
•Information

29. Four years running. Four books
Real-life use cases.
Experience with ACM.
http://AdaptiveCaseManagement.org/
Workflow Management Coalition
2014:
Thriving on
Adaptability:
Best
practices
for knowledge
workers

30. Workshop on Adaptive Case Management and other non- workflow approaches to BPM
2012 – Talinn Estonia, with BPM 2012
2013 - Graz , Austria, with OTM 2013
2014 – Ulm, Germany, with EDOC 2014
This continues to represent the leading research in ways to support unpredictable work patterns.

31. for interoperability
A Canonical Scenario

32. Canonical Scenario
Patient
Alex
Primary Doctor
Betty
Back Specialist
Charles
Physical Therapist
Dennis
1.Always specialists
2.Separate companies
3.Must coordinate
4.Info sensitive

33. Confer
Tests
Do
Do
Do
Primary Doctor
Meet
Research
Recommend
Back Specialist
Assess
Treat
Conclude
Physical Therapist

34. Personal Assistant

35. Personal Assistant

36. Personal Assistant

38. Complexity & Emergence

39. Simple Rules to Emergent Behavior
1.Bunch
2.Swoop
3.Swirl
1.Avoid hitting each other,
2.Stay near the flock,
3.Match velocity of neighbors.

40. Deriving Rules is Difficult or Impossible
1.Avoid hitting each other,
2.Stay near the flock,
3.Match velocity of neighbors.
1.Bunch
2.Swoop
3.Swirl
?

41. Maybe we are focusing on the wrong things?

42. Questions
Closed vs. Open systems
Monolithic System Assumption
Coherent Designer
Emergent Processes
Business Interaction Etiquette - not Protocols
e.g. Net 30 payment terms
Anti-fragile System Ideals
Personal Assistants

44. Cognoscenti
Open Source Project https://code.google.com/p/cognoscenti/
Test bed & reference implementation for:
Case exchange protocol
Federated case management
Personal assistant

45. Demo
Alex
Betty’s
Practice
Charles’ Practice
Dennis’
Space
Hosted on Cloud Server
Hosted on This Laptop
1.Personal Assistant helps coordinate communications
2.This is safer than email

46. Confer
Tests
Do
Do
Do
Primary Doctor
Primary Doctor
Back Specialist

47. Confer
Tests
Do
Do
Do
Primary Doctor
Personal
Assistant
What does it take to make this software act like a person?
Primary
Doctor
Back Specialist Personal Assistant

48. Case Cloning
Confer
Tests
Do
Do
Do
Primary Doctor
Meet
Research
Recommend
Back Specialist
Personal
Assistant

49. Cloning: copy documents & data
Confer
Tests
Do
Do
Do
Primary Doctor
Meet
Research
Recommend
Back Specialist
PA has to bring copies of DB and documents
Personal
Assistant

50. Confer
Tests
Do
Do
Do
Primary Doctor
Meet
Research
Recommend
Back Specialist
PA synchronizes
back when changed
within lower process
Personal
Assistant

51. Fan-out Problem – Interworking All
Many
Primary
Doctors
Many Back Specialists
Many
Physical
Therapists

52. Fan-out Problem – Interworking All
Many
Primary
Doctors
Many
Back
Specialists
Many
Physical
Therapists

53. Differing Representations of Patient
Primary
Doctor
Back Specialist
Physical
Therapist
Patient Info
Patient Info
Patient Info

54. Agent Must
Primary
Doctor
Back
Specialist
Physical Therapist
Patient Info
Patient Info
Patient Info
Transform
schema
between
levels
semantic mapping
semantic mapping
semantic mapping
possibly using mapping to standard ontology
Personal
Assistant
Personal
Assistant

55. Personal Assistant Can
Receive and screen notifications – filter the spam for relevant notifications.
Task Introduction – find offered tasks, gather additional information
Task Acceptance – sending a notice back to the sender.
Clone Project –automatically retrieve all the accessible.
Determine the Template –and start the process if necessary.
Synchronize – in both directions.
Transform Data – access the taxonomies that give the semantic meaning of the data, and use that to transform the data to a suitable form while synchronizing

56. Summary
In the future we might see
personal assistants interacting with other personal assistants,
cloning & synchronizing projects, and the large scale processes emerging from that interaction.

57. Questions?
Keith D Swenson Adaptive Case Management Get free chapter of new book at http://workcast.org/